scholarly journals Remote Sensing of Human–Environment Interactions in Global Change Research: A Review of Advances, Challenges and Future Directions

2019 ◽  
Vol 11 (23) ◽  
pp. 2783 ◽  
Author(s):  
Narcisa G. Pricope ◽  
Kerry L. Mapes ◽  
Kyle D. Woodward
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Global Change ◽  
Global Environmental Change ◽  
Human Dimensions ◽  
Sensor Technology ◽  
Unmanned Aerial Systems ◽  
Remotely Sensed Data ◽  
Human Environment ◽  
Landscape Degradation

The role of remote sensing and human–environment interactions (HEI) research in social and environmental decision-making has steadily increased along with numerous technological and methodological advances in the global environmental change field. Given the growing inter- and trans-disciplinary nature of studies focused on understanding the human dimensions of global change (HDGC), the need for a synchronization of agendas is evident. We conduct a bibliometric assessment and review of the last two decades of peer-reviewed literature to ascertain what the trends and current directions of integrating remote sensing into HEI research have been and discuss emerging themes, challenges, and opportunities. Despite advances in applying remote sensing to understanding ever more complex HEI fields such as land use/land cover change and landscape degradation, agricultural dynamics, urban geography and ecology, natural hazards, water resources, epidemiology, or paleo HEIs, challenges remain in acquiring and leveraging accurately georeferenced social data and establishing transferable protocols for data integration. However, recent advances in micro-satellite, unmanned aerial systems (UASs), and sensor technology are opening new avenues of integration of remotely sensed data into HEI research at scales relevant for decision-making purposes that simultaneously catalyze developments in HDGC research. Emerging or underutilized methodologies and technologies such as thermal sensing, digital soil mapping, citizen science, UASs, cloud computing, mobile mapping, or the use of “humans as sensors” will continue to enhance the relevance of HEI research in achieving sustainable development goals and driving the science of HDGC further.

The Human Dimensions of Global Change

2004 ◽  
Author(s):  
Diana Liverman ◽  
Brent Yarnal
Keyword(s):  
Global Change ◽  
Environmental Change ◽  
Large Scale ◽  
Information Science ◽  
Global Environmental Change ◽  
Human Dimensions ◽  
Water Diversion ◽  
Human Environment ◽  
Natural Systems ◽  
Global Environmental

The human–environment condition has emerged as one of the central issues of the new millennium, especially as it has become apparent that human activity is transforming nature at a global scale in both systemic and cumulative ways. Originating with concerns about potential climate warming, the global environmental change agenda rapidly enlarged to include changes in structure and function of the earth’s natural systems, notably those systems critical for life, and the policy implications of these changes, especially focused on the coupled human–environment system. Recognition of the unprecedented pace, magnitude, and spatial scale of global change, and of the pivotal role of humankind in creating and responding to it, has led to the emergence of a worldwide, interdisciplinary effort to understand the human dimensions of global change. The term “global change” now encompasses a range of research issues including those relating to economic, political, and cultural globalization, but in this chapter we limit our focus to global environmental change and to the field that has become formally known as the human dimensions of global (or global environmental) change. We also focus mainly on the work of geographers rather than attempting to review the whole human dimensions research community. Intellectually, geography is well positioned to contribute to global environmental change research (Liverman 1999). The large-scale human transformation of the planet through activities such as agriculture, deforestation, water diversion, fossil fuel use, and urbanization, and the impacts of these on living conditions through changes in, for example, climate and biodiversity, has highlighted the importance of scholarship that analyzes the human–environmental relationship and can inform policy. Geography is one of the few disciplines that has historically claimed human–environment relationships as a definitional component of itself (Glacken 1967; Marsh 1864) and has fostered a belief in and reward system for engaging integrative approaches to problem solving (Golledge 2002; Turner 2002). Moreover, global environmental change is intimately spatial and draws upon geography-led remote sensing and geographic information science (Liverman et al. 1998). Geographers anticipated the emergence of current global change concerns (Thomas et al. 1956; Burton et al. 1978) and were seminal in the development of the multidisciplinary programs of study into the human dimensions of global change.

scholarly journals Reflecting on the Anthropocene: The Call for Deeper Transformations

AMBIO ◽  
2021 ◽  
Author(s):  
Karen O’Brien
Keyword(s):  
Global Change ◽  
Environmental Change ◽  
Meaning Making ◽  
Global Environmental Change ◽  
50Th Anniversary ◽  
Human Environment ◽  
Cultural Narrative ◽  
Natural Systems ◽  
Global Change Research ◽  
Anniversary Issue

AbstractResearch on global environmental change has transformed the way that we think about human-environment relationships and Earth system processes. The four Ambio articles highlighted in this 50th Anniversary Issue have influenced the cultural narrative on environmental change, highlighting concepts such as “resilience,” “coupled human and natural systems”, and the “Anthropocene.” In this peer response, I argue that global change research is still paying insufficient attention to how to deliberately transform systems and cultures to avoid the risks that science itself has warned us about. In particular, global change research has failed to adequately integrate the subjective realm of meaning making into both understanding and action. Although this has been an implicit subtext in global change research, it is time to fully integrate research from the social sciences and environmental humanities.

Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters

1998 ◽  
Vol 22 (4) ◽  
pp. 449-476 ◽  
Author(s):  
Mike Wulder
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Forest Inventory ◽  
Management Practices ◽  
Structural Parameters ◽  
Remotely Sensed ◽  
Sensor Technology ◽  
Remotely Sensed Data ◽  
Biophysical Parameters ◽  
Processing Techniques

Forests are the most widely distributed ecosystem on the earth, affecting the lives of most humans daily, either as an economic good or an environmental regulator. As forests are a complex and widely distributed ecosystem, remote sensing provides a valuable means of monitoring them. Remote-sensing instruments allow for the collection of digital data through a range of scales in a synoptic and timely manner. Accordingly, a variety of image-processing techniques have been developed for the estimation of forest inventory and biophysical parameters from remotely sensed images. The use of remotely sensed images allows for the mapping of large areas efficiently and in a digital manner that allows for accuracy assessment and integration with geographic information systems. This article provides a summary of the image-processing methods which may be applied to remotely sensed data for the estimation of forest structural parameters while also acknowledging the various limitations that are presented. Current advancements in remote-sensor technology are increasing the information content of remotely sensed data and resulting in a need for new analysis techniques. These advances in sensor technology are occurring concurrently with changes in forest management practices, requiring detailed measurements intended to enable ecosystem-level management in a sustainable manner. This review of remote-sensing image analysis techniques, with reference to forest structural parameters, illustrates the dependence between spatial resolution to the level of detail of the parameters which may be extracted from remotely sensed imagery. As a result, the scope of a particular investigation will influence the type of imagery required and the limits to the detail of the parameters that may be estimated. The complexity of parameters that may be extracted can be increased through combinations of image-processing techniques. For example, multitemporal analysis of image radiance values or multispectral image classification maps may be analysed to undertake the assessment of such forest characteristics as area of forest disturbances, forest succession and development, or sustainability of forest management practices. Further, the combination of spectral and spatial information extraction techniques shows promise for increasing the accuracy of estimates of forest inventory and biophysical parameters.

THE ROLE OF REMOTE SENSING DATA FOR COASTAL ZONE MONITIORING AND MANAGEMENT (CASE STUDY FOR THE EAST PART OF GULF OF FINLAND)

2017 ◽  
Author(s):  
Nikifor Ostanin ◽  
Nikifor Ostanin
Keyword(s):  
Remote Sensing ◽  
Coastal Zone ◽  
Environmental Changes ◽  
Rapid Development ◽  
Water Environment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Gulf Of Finland ◽  
Coastal Protection ◽  
Remotely Sensed Data

Coastal zone of the Eastern Gulf of Finland is subjected to essential natural and anthropogenic impact. The processes of abrasion and accumulation are predominant. While some coastal protection structures are old and ruined the problem of monitoring and coastal management is actual. Remotely sensed data is important component of geospatial information for coastal environment research. Rapid development of modern satellite remote sensing techniques and data processing algorithms made this data essential for monitoring and management. Multispectral imagers of modern high resolution satellites make it possible to produce advanced image processing, such as relative water depths estimation, sea-bottom classification and detection of changes in shallow water environment. In the framework of the project of development of new coast protection plan for the Kurortny District of St.-Petersburg a series of archival and modern satellite images were collected and analyzed. As a result several schemes of underwater parts of coastal zone and schemes of relative bathymetry for the key areas were produced. The comparative analysis of multi-temporal images allow us to reveal trends of environmental changes in the study areas. This information, compared with field observations, shows that remotely sensed data is useful and efficient for geospatial planning and development of new coast protection scheme.

scholarly journals Imaging Spectroscopy for Conservation Applications

2021 ◽  
Vol 13 (2) ◽  
pp. 292
Author(s):  
Megan Seeley ◽  
Gregory P. Asner
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Case Studies ◽  
Spatial Scales ◽  
Imaging Spectroscopy ◽  
Remote Sensing Data ◽  
Decision Makers ◽  
High Spectral Resolution ◽  
Conservation Areas ◽  
Broad Array

As humans continue to alter Earth systems, conservationists look to remote sensing to monitor, inventory, and understand ecosystems and ecosystem processes at large spatial scales. Multispectral remote sensing data are commonly integrated into conservation decision-making frameworks, yet imaging spectroscopy, or hyperspectral remote sensing, is underutilized in conservation. The high spectral resolution of imaging spectrometers captures the chemistry of Earth surfaces, whereas multispectral satellites indirectly represent such surfaces through band ratios. Here, we present case studies wherein imaging spectroscopy was used to inform and improve conservation decision-making and discuss potential future applications. These case studies include a broad array of conservation areas, including forest, dryland, and marine ecosystems, as well as urban applications and methane monitoring. Imaging spectroscopy technology is rapidly developing, especially with regard to satellite-based spectrometers. Improving on and expanding existing applications of imaging spectroscopy to conservation, developing imaging spectroscopy data products for use by other researchers and decision-makers, and pioneering novel uses of imaging spectroscopy will greatly expand the toolset for conservation decision-makers.

scholarly journals Prediction of Ratoon Sugarcane Family Yield and Selection Using Remote Imagery

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1273
Author(s):  
James Todd ◽  
Richard Johnson
Keyword(s):  
Remote Sensing ◽  
Regression Model ◽  
Block Design ◽  
Color Space ◽  
Multiple Linear Regression Model ◽  
Cane Yield ◽  
Unmanned Aerial Systems ◽  
Family Selection ◽  
Ratoon Crop ◽  
Color Indices

Remote sensing techniques and the use of Unmanned Aerial Systems (UAS) have simplified the estimation of yield and plant health in many crops. Family selection in sugarcane breeding programs relies on weighed plots at harvest, which is a labor-intensive process. In this study, we utilized UAS-based remote sensing imagery of plant-cane and first ratoon crops to estimate family yields for a second ratoon crop. Multiple families from the commercial breeding program were planted in a randomized complete block design by family. Standard red, green, and blue imagery was acquired with a commercially available UAS equipped with a Red–Green–Blue (RGB) camera. Color indices using the CIELab color space model were estimated from the imagery for each plot. The cane was mechanically harvested with a sugarcane combine harvester and plot weights were obtained (kg) with a field wagon equipped with load cells. Stepwise regression, correlations, and variance inflation factors were used to identify the best multiple linear regression model to estimate the second ratoon cane yield (kg). A multiple regression model, which included family, and five different color indices produced a significant R2 of 0.88. This indicates that it is possible to make family selection predictions of cane weight without collecting plot weights. The adoption of this technology has the potential to decrease labor requirements and increase breeding efficiency.

scholarly journals Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3982
Author(s):  
Giacomo Lazzeri ◽  
William Frodella ◽  
Guglielmo Rossi ◽  
Sandro Moretti
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Fire Severity ◽  
Experimental Methodology ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
The Impact ◽  
Sentinel 2

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

scholarly journals Quantitative Analysis of the Research Trends and Areas in Grassland Remote Sensing: A Scientometrics Analysis of Web of Science from 1980 to 2020

2021 ◽  
Vol 13 (7) ◽  
pp. 1279
Author(s):  
Tong Li ◽  
Lizhen Cui ◽  
Zhihong Xu ◽  
Ronghai Hu ◽  
Pawan K. Joshi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sustainable Development ◽  
Web Of Science ◽  
Temporal Trends ◽  
Research Trends ◽  
Annual Number ◽  
Unmanned Aerial Systems ◽  
Comprehensive Overview ◽  
Research Areas ◽  
Research Studies

Grassland remote sensing (GRS) is an important research topic that applies remote sensing technology to grassland ecosystems, reflects the number of grassland resources and grassland health promptly, and provides inversion information used in sustainable development management. A scientometrics analysis based on Science Citation Index-Expanded (SCI-E) was performed to understand the research trends and areas of focus in GRS research studies. A total of 2692 papers related to GRS research studies and 82,208 references published from 1980 to 2020 were selected as the research objects. A comprehensive overview of the field based on the annual documents, research areas, institutions, influential journals, core authors, and temporal trends in keywords were presented in this study. The results showed that the annual number of documents increased exponentially, and more than 100 papers were published each year since 2010. Remote sensing, environmental sciences, and ecology were the most popular Web of Science research areas. The journal Remote Sensing was one of the most popular for researchers to publish documents and shows high development and publishing potential in GRS research studies. The institution with the greatest research documents and most citations was the Chinese Academy of Sciences. Guo X.L., Hill M.J., and Zhang L. were the most productive authors across the 40-year study period in terms of the number of articles published. Seven clusters of research areas were identified that generated contributions to this topic by keyword co-occurrence analysis. We also detected 17 main future directions of GRS research studies by document co-citation analysis. Emerging or underutilized methodologies and technologies, such as unmanned aerial systems (UASs), cloud computing, and deep learning, will continue to further enhance GRS research in the process of achieving sustainable development goals. These results can help related researchers better understand the past and future of GRS research studies.

scholarly journals Snow dunes and glazed surfaces in Antarctica: new field and remote-sensing data

2002 ◽  
Vol 34 ◽  
pp. 81-88 ◽  
Author(s):  
Massimo Frezzotti ◽  
Stefano Gandolfi ◽  
Floriana La Marca ◽  
Stefano Urbini
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Accumulation Rate ◽  
Spectral Response ◽  
Remote Sensing Data ◽  
Snow Accumulation ◽  
Remotely Sensed Data ◽  
Surface Mass ◽  
Glazed Surface ◽  
Transverse Dunes

AbstractAs part of the International Trans-Antarctic Scientific Expedition project, the Italian Antarctic Programme undertook two traverses from the Terra Nova station to Talos Dome and to Dome C. Along the traverses, the party carried out several tasks (drilling, glaciological and geophysical exploration). The difference in spectral response between glazed surfaces and snow makes it simple to identify these areas on visible/near-infrared satellite images. Integration of field observation and remotely sensed data allows the description of different mega-morphologic features: wide glazed surfaces, sastrugi glazed surface fields, transverse dunes and megadunes. Topography global positioning system, ground penetrating radar and detailed snow-surface surveys have been carried out, providing new information about the formation and evolution of mega-morphologic features. The extensive presence, (up to 30%) of glazed surface caused by a long hiatus in accumulation, with an accumulation rate of nil or slightly negative, has a significant impact on the surface mass balance of a wide area of the interior part of East Antarctica. The aeolian processes creating these features have important implications for the selection of optimum sites for ice coring, because orographic variations of even a few metres per kilometre have a significant impact on the snow-accumulation process. Remote-sensing surveys of aeolian macro-morphology provide a proven, high-quality method for detailed mapping of the interior of the ice sheet’s prevalent wind direction and could provide a relative indication of wind intensity.

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